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1.
Income inequality, primary care, and health indicators   总被引:15,自引:0,他引:15  
BACKGROUND: The significant association of income inequality with a variety of health indicators is receiving increasing attention. There has also been increasing evidence of a link between primary care and improved health status. We examined the joint relationship between income inequality, availability of primary care, and various health indicators to determine whether primary care has an impact on health indicators by modifying the adverse effect of income inequality. METHODS: Our ecologic study used the US states as the units of analysis. In analyzing the data, we looked at the associations among income inequality, primary care, specialty care, smoking, and health indicators, using Pearson's correlation coefficients for intercorrelations and the adjusted multiple regression procedure. To examine the effect of inequality and primary care on health outcome indicators, we conducted path analyses according to a causal model in which inequality affects health both directly and indirectly through its impact on primary care. RESULTS: Our study indicates that both primary care and income inequality exerted a strong and significant direct influence on life expectancy and total mortality (P <.01). Primary care also exerted a significant direct influence on stroke and postneonatal mortality (P <.01). Although levels of smoking are also influential, the effect of income inequality and primary care persists after controlling for smoking. Primary care serves as one pathway through which income inequality influences population-level mortality and at least some other health outcome indicators. CONCLUSIONS: It appears possible that a primary care orientation may, in part, overcome the severe adverse effects on health of income inequalities.  相似文献   

2.
Using the 1996 Community Tracking Study household survey, the authors examined whether income inequality and primary care, measured at the state level, predict individual morbidity as measured by self-rated health status, while adjusting for potentially confounding individual variables. Their results indicate that distributions of income and primary care within states are significantly associated with individuals' self-rated health; that there is a gradient effect of income inequality on self-rated health; and that individuals living in states with a higher ratio of primary care physician to population are more likely to report good health than those living in states with a lower such ratio. From a policy perspective, improvement in individuals' health is likely to require a multi-pronged approach that addresses individual socioeconomic determinants of health, social and economic policies that affect income distribution, and a strengthening of the primary care aspects of health services.  相似文献   

3.
OBJECTIVE: To examine the extent to which good primary-care experience attenuates the adverse association of income inequality with self-reported health. DATA SOURCES: Data for the study were drawn from the Robert Wood Johnson Foundation sponsored 1996-1997 Community Tracking Study (CTS) Household Survey and state indicators of income inequality and primary care. STUDY DESIGN: Cross-sectional, mixed-level analysis on individuals with a primary-care physician as their usual source of care. The analyses were weighted to represent the civilian noninstitutionalized population of the continental United States. DATA COLLECTION/EXTRACTION METHODS: Principal component factor analysis was used to explore the stricture of the primary-care indicators and examine their construct validity. Income inequality for the state in which the community is located was measured by the Gini coefficient, calculated using income distribution data from the 1996 current population survey. Stratified analyses compared proportion of individuals reporting had health and feeling depressed with those with good and bad primary-care experiences for each of the four income-inequality strata. A set of logistic regressions were performed to examine the relation between primary-care experience, income inequality, and self-rated health. PRINCIPAL FINDINGS: Good primary-care experience, in particular enhanced accessibility and continuity, was associated with better self-reported health both generally and mentally. Good primary-care experience was able to reduce the adverse association of income inequality with general health although not with mental health, and was especially beneficial in areas with highest income inequality. Socioeconomic status attenuated, but did not eliminate, the effect of primary-care experience on health. In conclusion, good primary-care experience is associated not only with improved self-rated overall and mental health but also with reductions in disparities between more- and less-disadvantaged communities in ratings of overall health.  相似文献   

4.
OBJECTIVE: The objective of this study was to test whether the association between primary care and income inequality on all-cause, heart disease and cancer mortality at county level differs in urban (Metropolitan Statistical Area-MSA) compared with non-urban (non-MSA) areas. STUDY DESIGN: The study consisted of a cross-sectional analysis of county-level data stratified by MSA and non-MSA areas in 1990. Dependent variables included age and sex-standardized (per 100,000) all-cause, heart disease and cancer mortality. Independent variables included primary care resources, income inequality, education levels, unemployment, racial/ethnic composition and income levels. METHODS: One-way analysis of variance and multivariate ordinary least squares regression were employed for each health outcome. RESULTS: Among non-MSA counties, those in the highest income inequality category experienced 11% higher all-cause mortality, 9% higher heart disease mortality, and 9% higher cancer mortality than counties in the lowest income inequality quartile, while controlling for other health determinants. Non-MSA counties with higher primary care experienced 2% lower all-cause mortality, 4% lower heart disease mortality, and 3% lower cancer mortality than non-MSA counties with lower primary care. MSA counties with median levels of income inequality experienced approximately 6% higher all-cause mortality, 7% higher heart disease mortality, and 7% higher cancer mortality than counties in the lowest income inequality quartile. MSA counties with low primary care (less than 75th percentile) had significantly lower levels of all-cause, heart disease and cancer mortality than those counties with high primary care. CONCLUSIONS: In non-MSA counties, increasing primary physician supply could be one way to address the health needs of rural populations. In MSA counties, the association between primary care and health outcomes appears to be more complex and is likely to require intervention that focuses on multiple fronts.  相似文献   

5.
Levels of health development are formed by mathematically clustering countries using six health status indicators: crude birth, crude death, infant mortality and child death rates, and male and female life expectancy. Stratifying two international samples of 128 and 163 countries into levels of health development--groups with similar health status profiles--improves the results of regression analyses used to identify economic, political, social, educational, health and other health determinants. For this reason, health development levels are a systematic framework for delineation of health determinants. Earlier large scale statistical studies have been limited in their success in part because they did not partition their data sets prior to analysis, or used inappropriate criteria that blurred rather than heightened developmental differences in underlying social systems. These developmental differences regulate the way in which health status inputs are converted into health status outputs, defining the relative importance of health determinants at various developmental levels. At lowest health development levels (countries with poorer health status), the under-development of economic, health and educational infrastructures creates a vacuum which allows international intervention (aid, investment, export/import activities) to play a dominant role in health status determination. At middle health development levels, health and educational infrastructures are better developed, but still secondary in importance as health status determinants to basic economic infrastructure. Demographic problems are particularly apparent at these levels. At higher health development levels, education, women's status, and political structure are especially important health status determinants. This research has facilitated the identification of health status determinants for use in health policy analysis. Recommendations for future research include use of findings in health policymaking by individual countries and by comparative researchers, and development of appropriate health systems models for each level of health development.  相似文献   

6.
Results from the Joint Canada/United States Survey of Health (2002-2003) reveal that health status is relatively similar in the two countries, but income-related health disparities exist. Americans in the poorest income quintile are more likely to have poor health than their Canadian counterparts; there were no differences between the rich. In general, Canadians were more like insured Americans regarding access to services, and Canadians experienced fewer unmet needs overall. Despite higher U.S. levels of spending on health care, residents in the two countries have similar health status and access to care, although there are higher levels of inequality in the United States.  相似文献   

7.
OBJECTIVES: This study assessed whether income inequality and primary care physician supply have a different effect on mortality among Blacks compared with Whites. METHODS: We conducted a multivariate ecologic analysis of 1990 data from 273 US metropolitan areas. RESULTS: Both income inequality and primary care physician supply were significantly associated with White mortality (P < .01). After the inclusion of the socioeconomic status covariates, the effect of income inequality on Black mortality remained significant (P < .01), but the effect of primary care physician supply was no longer significant (P > .10), particularly in areas with high income inequality. CONCLUSIONS: Improvement in population health requires addressing socioeconomic determinants of health, including income inequality and primary care availability and access.  相似文献   

8.
The income elasticity of health care spending in the OECD countries tends toward luxury good values. Similar studies, based on more recent data, and capable of informing macroeconomic health policies of the African countries, do not currently exist. How the health care expenditure in Africa responds to changes in the Gross Domestic Products (GDP), Official Development Assistance (ODA), and other determinants, is also relevant for health policy because health care is a necessity in the ‘basic needs’ theory of economic development. This paper presents econometric model findings of the determinants of per-capita health expenditure (in PPPs) for 26 African countries, using the flexible Box-Cox model regression methods and 1995 cross-sectional data (sources: WRI, UNEP, UNDP, The World Bank). The economic and other determinants, capturing 74 percent of the variations in health expenditures, include per-capita GDP (in PPPs), ODA (US$), Gini income inequality index, population dependency ratio, internal conflicts, and the percentage of births attended by trained medical workers. Income inequality dampens, while the ODA and population per health personnel raise health care expenditure. The GDP elasticity of about 0.6 signals the tendency for health care to behave like a technical ‘necessity.’ Implications for sustainable basic health development policies are discussed.  相似文献   

9.
This article describes U.S. income inequality and 100-year national and 30-year regional trends in age- and cause-specific mortality. There is little congruence between national trends in income inequality and age- or cause-specific mortality except perhaps for suicide and homicide. The variable trends in some causes of mortality may be associated regionally with income inequality. However, between 1978 and 2000 those regions experiencing the largest increases in income inequality had the largest declines in mortality (r= 0.81, p < 0.001). Understanding the social determinants of population health requires appreciating how broad indicators of social and economic conditions are related, at different times and places, to the levels and social distribution of major risk factors for particular health outcomes.  相似文献   

10.
Income inequality is very topical—in both political and economic circles—but although income and socioeconomic status are known determinants of health status, income inequality has garnered scant attention with respect to the health of US workers. By several measures, income inequality in the United States has risen since 1960. In addition to pressures from an increasingly competitive labor market, with cash wages losing out to benefits, workers face pressures from changes in work organization.We explored these factors and the mounting evidence of income inequality as a contributing factor to poorer health for the workforce.Although political differences may divide the policy approaches undertaken, addressing income inequality is likely to improve the overall social and health conditions for those affected.Income inequality in the United States is now a common theme in national policy debates, and both major parties are seemingly embracing the need to address it, although their messaging and the degree of importance they assign to the issue vary significantly.1,2 Although income itself and the broader construct of socioeconomic status are known key determinants of health status, income inequality has garnered scant attention with respect to health in general and with respect to the health of US workers specifically.Because income inequality is inexorably linked to employment, a more complete picture of the effects of inequality on health emerges when analyzed through the lens of the working population. Moreover, differences in income are associated with differences in occupations and work environments, potentially exacerbating the overall effect of income inequality on workers’ health.We considered trends in US workforce composition, income inequality, and work organization; how income inequality alone and together with income status affects health; and exemplary issues facing the large and growing health care workforce.  相似文献   

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